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Employee turnover is an unavoidable part of business development, costing important human resources and impeding long-term growth and strategy implementation. To maintain a steady workforce, businesses must prioritize understanding and addressing this issue. The objective of this study is to examine the impact of leadership style, career development, and work stress on turnover intention in the high-tech industry and to investigate the moderating role of psychological contracts in these relationships. The sample consists of 380 employees of the R&D departments in high-tech companies in Shenzhen, Guangdong province, China, mainly engaged in the electronic information, advanced manufacturing, and automation sectors. The data were gathered via an online questionnaire, and the Smart-PLS approach was used to analyze the data. The empirical findings indicate that transactional leadership, transformational leadership, and career development are significantly and negatively related to turnover intention, whereas work stress has a significant positive effect. The psychological contract moderates the relationship between career development and turnover intention; the higher the psychological contract, the stronger the relationship. In addition, the psychological contract moderates the relationship between work stress and turnover intention, whereby the higher the psychological contract, the weaker the relationship. However, no empirical evidence suggests that the psychological contract moderates the relationship between leadership styles and turnover intention. The R² value is 0.485, indicating moderate explanatory power, and with a GOF index of 0.492, the model also demonstrates a good fit with the data. This study offers considerable implications for both theoretical and practical applications.

In the power system, power marketing is a very important work. How to evaluate whether the currently used power marketing strategy is efficient and useful has always been the most important concern of the power system. This paper proposes an efficient electricity marketing strategy evaluation method based on multi-dimensional clustering algorithm, aiming to evaluate whether a new policy has an incentive effect on enterprises through the means of big data. First, we use big data to group motivated users, and then analyze the effect of personalized marketing and key marketing on target customer groups. Based on the existing marketing methods, the influence of different target groups is analyzed, and finally the feasibility of the proposed method is verified through two experiments. In the A and B companies selected in Experiment 1, the average errors of the predicted value and the actual value are 1.4% and 1.2%, respectively. For the 12 industries in the C area selected in experiment 2, the average error between the predicted value and the actual value is 0.55%. Both experiments show that the method proposed in this paper has certain applicability. The method in this paper can be applied to the marketing process of the power supply company, and the corresponding promotion strategy is put forward, which is helpful to improve the management level of the power supply enterprise and increase the economic income of the power supply enterprise.

The novel coronavirus disease 2019 (COVID-19) rapidly escalated to a global pandemic. To control the rate of transmission, governments advocated that the public practice social distancing, which included staying at home. However, compliance with stay-at-home orders has varied between countries such as China and the United States, and little is known about the mechanisms underlying the national differences. Based on the health belief model, the theory of reasoned action, and the technology acceptance model, health beliefs and behavioral intention are suggested as possible explanations. A total of 498 Chinese and 292 American college students were recruited to complete an online survey. The structural equation modeling results showed that health beliefs (i.e., perceived susceptibility, severity, and barriers) and behavioral intention played multiple mediating roles in the association between nationality and actual stay-at-home behaviors. Notably, the effect via perceived barriers → behavioral intention was stronger than the effects via perceived susceptibility and severity → behavioral intention. That is, American participants perceived high levels of susceptibility whereas Chinese participants perceived high levels of severity, especially few barriers, which further led to increased behavioral intention and more frequent stay-at-home behaviors. These findings not only facilitate a comprehensive understanding of cross-country differences in compliance with stay-at-home orders during peaks in the COVID-19 pandemic but also lend support for mitigation of the current global crisis and future disease prevention and health promotion efforts.

The technology acceptance model (TAM) has been regarded as a promising model for understanding technology adoption and can be extended to different situations. Currently, mobile payment services have been widely applied in people's daily lives in China, and understanding their critical success factors is becoming important. Mobile payments are a complex system, and a large number of factors affect their success. Since mobile payments are directly related to financial issues, their wide adoption relies heavily on people's trust. We developed a model based on the TAM to investigate the most influential factors in building trust within the mobile payment context. We conducted an empirical survey and 373 samples were collected using a valid questionnaire from the users of the popular payment platforms in China—Alipay and WeChat payment. We found that government monitoring is the most significant factor of customer trust, followed by reputation, and security. Government monitoring directly influenced behavioral intention, was negatively associated with perceived risk and positively affected behavioral intention. Moreover, mobility, subjective norms, usefulness, ease of use, and perceived enjoyment impacts customer behavioral intention.

Xiao-hu Nie,1,* Jia Ou-yang,2,* Ying Xing,3 Dan-yan Li,4 Ru-en Liu,5 Ru-xiang Xu6 1Department of Neurosurgery, Huzhou Central Hospital, Huzhou, Zhejiang, 2Nanchang University Medical College, Nanchang, Jiangxi, 3Department of Gastroenterology, The 98th Hospital of Nanjing Military Command, Huzhou, Zhejiang, 4Spleen & Stomach Institute, Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 5Department of Neurosurgery, China–Japan Friendship Hospital, Beijing, 6Bayi Brain Hospital, The Military General Hospital of Beijing PLA, Beijing, People's Republic of China *These authors contributed equally to this work Abstract: In this study, we investigated the potential anticancer effects of calycosin against human glioblastoma cells, including the impacts on cell proliferation, apoptosis, and cell cycle distribution. We further studied its inhibitory activity on migration and invasion in U87 and U251 cells. Furthermore, transforming growth factor beta-mediated reductions of mesenchymal-associated genes/activators, matrix metalloproteinases-2, and -9 were detected in this process. Administration of calycosin in a glioblastoma xenograft model showed that calycosin could not only reduce tumor volume but also suppress transforming growth factor beta as well as its downstream molecules. These results revealed calycosin as a potential antitumor agent in human glioblastoma. Keywords: calycosin, migration, invasion, epithelial–mesenchymal transition (EMT), matrix metalloproteinases (MMPs), glioblastoma

The paper examined the relations among problem solving, automaticity, and working memory load (WML) by changing the difficulty level of task characteristics through two applications. In Study 1, involving 68 engineering students, a 2 (automaticity) × 2 (WML) design was utilized for arithmetic problems. In Study 2, involving 76 engineering students, a 2 (automaticity) × 2 (WML) design was used for linear algebra tasks. In both studies, there were statistically significant main effects and interaction effects of automaticity and WML on the variable of response time, concurring with the cognitive load theory. The simple effect of WML rendered a larger effect size under the conditions with low automaticity. When the testing condition was easy but contained more steps, the students were more accurate, and response times were faster. When the testing condition was difficult but contained fewer steps, the students were less accurate, and response times were slower. The findings underscore the important role of automaticity in helping engineering students bypass the limits of working memory.

Xiao-hu Nie,1,* Jia Ou-yang,2,* Ying Xing,3 Dan-yan Li,4 Xing-yu Dong,1 Ru-en Liu,5 Ru-xiang Xu6 1Affiliated Bayi Brain Hospital, Southern Medical University, Beijing, People's Republic of China; 2Nanchang University Medical College, Jiangxi, People's Republic of China; 3Department of Gastroenterology, The 98th Hospital of Nanjing Military Command, Huzhou, Zhejiang, People's Republic of China; 4Spleen & Stomach Institution, Guangzhou University of Traditional Chinese Medicine, Guangdong, People's Republic of China; 5Department of Neurosurgery, China–Japan Friendship Hospital, Beijing, People's Republic of China; 6Bayi Brain Hospital, The Military General Hospital of Beijing PLA, Beijing, People's Republic of China *These authors contributed equally to this work Abstract: We investigated the underlying mechanism for the potent proapoptotic effect of paeoniflorin (PF) on human glioma cells in vitro, focusing on signal transducer and activator of transcription 3 (STAT3) signaling. Significant time- and dose-dependent apoptosis and inhibition of proliferation were observed in PF-treated U87 and U251 glioma cells. Expression of STAT3, its active form phosphorylated STAT3 (p-STAT3), and several downstream molecules, including HIAP, Bcl-2, cyclin D1, and Survivin, were significantly downregulated upon PF treatment. Overexpression of STAT3 induced resistance to PF, suggesting that STAT3 was a critical target of PF. Interestingly, rapid downregulation of STAT3 was consistent with its accelerated degradation, but not with its dephosphorylation or transcriptional modulation. Using specific inhibitors, we demonstrated that the prodegradation effect of PF on STAT3 was mainly through the ubiquitin–proteasome pathway rather than via lysosomal degradation. These findings indicated that PF-induced growth suppression and apoptosis in human glioma cells through the proteasome-dependent degradation of STAT3. Keywords: paeoniflorin, glioma, apoptosis, proliferation, signal transducer and activator of transcription 3 (STAT3), ubiquitin–proteasome pathway (UPP)